59 citations · 91 across the 6 of their papers we have counts for
6 papers
Simulation Model Calibration with Dynamic Stratification and Adaptive Sampling
Pranav Jain, Sara Shashaani, Eunshin Byon
Calibrating simulation models that take large quantities of multi-dimensional data as input is a hard simulation optimization problem. Existing adaptive sampling strategies offer a…
Distributionally Robust Stratified Sampling for Stochastic Simulations with Multiple Uncertain Input Models
Seung Min Baik, Eunshin Byon, Young Myoung Ko
This paper presents a robust version of the stratified sampling method when multiple uncertain input models are considered for stochastic simulation. Various variance reduction tec…
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning
Raed Kontar, Naichen Shi, Xubo Yue +12
The Internet of Things (IoT) is on the verge of a major paradigm shift. In the IoT system of the future, IoFT, the cloud will be substituted by the crowd where model training is br…
An Alternative Data-Driven Prediction Approach Based on Real Option Theories
Abdullah AlShelahi, Jingxing Wang, Mingdi You +2
This paper presents a new prediction model for time series data by integrating a time-varying Geometric Brownian Motion model with a pricing mechanism used in financial engineering…
Integrative Density Forecast and Uncertainty Quantification of Wind Power Generation
Jingxing Wang, Abdullah Alshelahi, Mingdi You +2
The volatile nature of wind power generation creates challenges in achieving secure power grid operations. It is, therefore, necessary to make accurate wind power prediction and it…
Bayesian spline method for assessing extreme loads on wind turbines
Giwhyun Lee, Eunshin Byon, Lewis Ntaimo +1
This study presents a Bayesian parametric model for the purpose of estimating the extreme load on a wind turbine. The extreme load is the highest stress level imposed on a turbine…